Images of scenes captured in bad weather conditions, such as in fog and sandstorm, may have poor contrasts and colors. Various types of techniques for restoring images from these weather-degraded images are known; these types of techniques are used for, for example, driver assistance systems to be installed in motor vehicles.
One type of the techniques is disclosed in US patent application Publication No. 2008/0317287 corresponding to Japanese Patent Application Publication No. 2008-310509.
The technique disclosed in the patent Publication applies Kalman filter processing to each of successive fog-affected images of a target; these successive fog-affected images are captured by a camera located above a road plane.
The Kalman filter defines, as a measurement (observation) vector, a luminance level (corresponding to a light intensity level) of each pixel of a fog-affected image (input image), and, as a state vector, an intrinsic luminance level of each pixel of the input image. The Kalman filter also defines an observation (measurement) matrix established based on parameters (deterioration parameters) representing a degree of deterioration of the luminance level of each pixel of the input image. The Kalman filter further defines a state transition matrix expressing changes that occur in the state vector during an interval between acquiring successive fog-affected images.
Specifically, the technique is configured to apply the Kalman filter processing to each of the successive fog-affected images to thereby obtain predicted levels of the state vector. The predicted levels of the state vector constitute a restored image having effects of fog substantially removed.